We propose a new approach for the self-selection of optimized gene-specific inhibitors based on RNA Lasso libraries. Lassos are RNA molecules that hybridize to and become topologically linked with target RNA molecules, creating complexes with superior stability and specificity as compared to currently available antisense compounds. RNA Lassos can be employed either to inhibit the expression of genes or as probes to detect the presence of particular polynucleotide sequences associated with a disease. A major challenge in all antisense approaches is finding "antisensitive" sequences on target mRNAs. Our approach allows automatic selection of both accessible target sites and optimal Lasso sequences. We describe the design of RNA Lasso libraries that incorporate gene-specific, directed antisense libraries along with a partially randomized Lasso sequence. Lassos will be selected that are linear in the absence of the target, but are activated to undergo self-ligation upon binding to a target sequence, creating a strong, topologically linked complex. These selected Lassos will be then tested for their ability to inhibit translation of the target mRNA. In this way, optimized Lassos will be derived in an automatic and straightforward manner for application as agents for target validation, gene function analysis, and therapeutics.